Weather radar systems currently perform ground clutter filtering at locations indicated by predetermined ground clutter maps. The current filtering procedure operates on powers of a Doppler spectral component and comprises the following steps: rank-ordering power spectral coefficients to assess spectral noise and clutter statistics, modeling of an expected ground clutter return, removing spectral coefficients identified as clutter, and fitting a Gaussian curve to replace removed coefficients with the goal of reconstructing weather contribution. The current ground clutter filtering procedure is inadequate for dual-polarization weather radar systems. Dual-polarization weather radar systems sense the atmosphere using horizontally and vertically polarized waves and therefore obtain two sets of data compared to the one set in legacy systems. The differences and correlations between the horizontal and vertical returns provide information about the shape and scattering properties of illuminated media, which are used for echo classification. These differences and correlations are expressed in terms of dual-polarization variables. Several dual-polarization variables, including differential phase and co-polar correlation coefficient cannot be estimated from powers and instead must be estimated from complex-valued radar returns. Because existing ground clutter filters operate on powers and not on complex-valued coefficients some dual-polarization variables cannot be determined. One method for recovering the dual polarization variables involves notching a portion of the spectra that has been identified to have a clutter contribution and estimating polarimetric variables from the remaining spectral coefficients. However, this approach cannot be used if clutter width is large and if there is a significant overlay between clutter and weather contributions in a Doppler spectral component. Notching also introduces an undesirable bias since only a portion of the spectra can be processed. Improvements to existing systems for performing ground clutter filtering are thus desired.